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Gravitre
AI agents that learn your business, not just tasks
Gravitre pairs AI agents and workflows with GIBE (Gravitre Intelligent Business Engine), a machine learning engine that learns your business logic over time plus 50+ tool integrations (and counting) and enterprise governance, deployed in minutes.
Most AI agent platforms are really just static scripts with an LLM wrapper. They execute the same way on run 1 and run 100, no matter what they learn along the way. That felt like a missed opportunity, so Gravitre is built around GIBE, a machine learning engine that sits underneath every agent and workflow.
GIBE learns your actual business logic as agents run. Which leads convert, which outreach patterns work, which workflows need a human check versus which can run autonomously. It uses that to improve confidence scoring and decision making over time. It's the difference between an agent that follows instructions and one that gets sharper the longer it works with your data.
On top of that, there's a marketplace of pre-built, role-ready agent and workflow templates connecting to 50+ tools like Salesforce, HubSpot, Apollo, Slack, and Jira via OAuth. No manual wiring, no coding. Enterprise-grade governance and approval gates mean autonomy doesn't come at the cost of control.
One more thing that matters to me in a category full of inflated claims: every run reports exactly what happened. Verified activity, labeled estimates, and anything unmeasured left open rather than invented.
Built solo, bootstrapped, no funding. Would love your feedback on the ML approach, the governance model, any of it.
About Gravitre on Product Hunt
“AI agents that learn your business, not just tasks”
Gravitre was submitted on Product Hunt and earned 3 upvotes and 1 comments, placing #102 on the daily leaderboard. Gravitre pairs AI agents and workflows with GIBE (Gravitre Intelligent Business Engine), a machine learning engine that learns your business logic over time plus 50+ tool integrations (and counting) and enterprise governance, deployed in minutes.
On the analytics side, Gravitre competes within SaaS, Artificial Intelligence and Tech — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Gravitre performed against the three products that launched closest to it on the same day.
Who hunted Gravitre?
Gravitre was hunted by Cesar Bohorquez Jr.. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Gravitre including community comment highlights and product details, visit the product overview.
Hey everyone, Cesar here.
Most AI agent platforms are really just static scripts with an LLM wrapper. They execute the same way on run 1 and run 100, no matter what they learn along the way. That felt like a missed opportunity, so Gravitre is built around GIBE, a machine learning engine that sits underneath every agent and workflow.
GIBE learns your actual business logic as agents run. Which leads convert, which outreach patterns work, which workflows need a human check versus which can run autonomously. It uses that to improve confidence scoring and decision making over time. It's the difference between an agent that follows instructions and one that gets sharper the longer it works with your data.
On top of that, there's a marketplace of pre-built, role-ready agent and workflow templates connecting to 50+ tools like Salesforce, HubSpot, Apollo, Slack, and Jira via OAuth. No manual wiring, no coding. Enterprise-grade governance and approval gates mean autonomy doesn't come at the cost of control.
One more thing that matters to me in a category full of inflated claims: every run reports exactly what happened. Verified activity, labeled estimates, and anything unmeasured left open rather than invented.
Built solo, bootstrapped, no funding. Would love your feedback on the ML approach, the governance model, any of it.